5 citations · 13 across the 4 of their papers we have counts for
4 papers
SegVisRL: Visuomotor Development for a Lunar Rover for Hazard Avoidance using Camera Images
Tamir Blum, Gabin Paillet, Watcharawut Masawat +2
The visuomotor system of any animal is critical for its survival, and the development of a complex one within humans is large factor in our success as a species on Earth. This syst…
RL STaR Platform: Reinforcement Learning for Simulation based Training of Robots
Tamir Blum, Gabin Paillet, Mickael Laine +1
Reinforcement learning (RL) is a promising field to enhance robotic autonomy and decision making capabilities for space robotics, something which is challenging with traditional te…
PPMC RL Training Algorithm: Rough Terrain Intelligent Robots through Reinforcement Learning
Tamir Blum, Kazuya Yoshida
Robots can now learn how to make decisions and control themselves, generalizing learned behaviors to unseen scenarios. In particular, AI powered robots show promise in rough enviro…
Deep Learned Path Planning via Randomized Reward-Linked-Goals and Potential Space Applications
Tamir Blum, William Jones, Kazuya Yoshida
Space exploration missions have seen use of increasingly sophisticated robotic systems with ever more autonomy. Deep learning promises to take this even a step further, and has app…